Figure S1: P maps of differences between groups in thickness of gray matter for. the subgroup of 16 Pure Tourette syndrome subjects and their age and

Transcription

1 Cortical Thickness in Tourette Syndrome Figure Legends: Figure S1: P maps of differences between groups in thickness of gray matter for the subgroup of 16 Pure Tourette syndrome subjects and their age and gender matched controls. Regions in red are statistically significant (uncorrected) at a p value < Regions in purple or pink do not approach significance, with p values approaching 1.0. Central, precentral, and postcentral sulci, which bound the precentral and postcentral gyri, and the inferior frontal sulcus and Sylvian fissure, are superimposed in black. Precentral gyrus (PreCG), postcentral gyrus (PostCG), parietal cortex (P), temporal cortex (T), occipital cortex (Occ), Broca s area (BA), dorsal frontal (DF), dorsal medial frontal (DMF) and the subgenual (SG) region are shown where appropriate with lines leading to the relevant regions of the statistical maps.

2 Cortical Thickness in Tourette Syndrome Figure S2: Statistical P maps of the age x group interaction in predicting cortical thickness. Color coding and abbreviations are the same as those described for Figure S1.

3 Cortical Thickness in Tourette Syndrome Table S1: Permutation Test Results: Permutation test results are shown for all lateral regions of interest that were significant for decreased cortical thickness in the Pure Tourette syndrome relative to the control group, or at trend level significance. Also shown are permutation test results for age by group interactions. The P values shown reflect the likelihood of observing the number of significant (at p = 0.05) surface points within each ROI by chance upon 10,000 randomizations. Permutation results for medial ROIs were significant only for the left medial dorsal frontal region in the symptom severity vs. thickness analyses (p = ), and thus are not shown for the other non significant medial ROIs. NS stands for non significant. Table S1: Permutation Test Results for Cortical Thickness Analyses Pure Diagnosis vs. Control Age Group interaction with Intelligence Quotient thickness Corrected N=35 N=70 Region of Interest Lateral Left Right Left Right Dorsal Frontal ns ns ns Ventral Frontal ns ns Parietal ns Occipital ns Temporal ns ns ns

4 THINNING OF SENSORIMOTOR CORTICES IN CHILDREN WITH TOURETTE SYNDROME Elizabeth R. Sowell, Ph.D. 1, Eric Kan, B.S. 1, June Yoshii, B.S. 1, Paul M. Thompson, Ph.D. 1, Ravi Bansal, Ph.D., 2 Dongrong Xu, Ph.D., 2 Arthur W. Toga, Ph.D. 1, and Bradley S. Peterson, M.D. 2 Supplementary Online Methods Participants METHODS Twenty five children and adolescents (mean age 12.4 years, 7 to 18 years, 7 female) who met DSM IV criteria for a diagnosis of Tourette disorder were recruited from the Tic Disorder Clinic at the Yale Child Study Center. Five had a secondary diagnosis of combined type attention deficit/hyperactivity disorder (ADHD) and 4 had a diagnosis of obsessive compulsive disorder (OCD). Subjects were excluded if they had neurological illness, another movement disorder, a history of seizures or head trauma with loss of consciousness, ongoing substance abuse or previous substance dependence, or an intelligence quotient below 80. Diagnoses were established by using the Schedule for Tourette and Other Behavioral Syndromes 1, which includes the Schedule for Affective Disorders and Schizophrenia for School Age Children Present and Lifetime Version 2, and the best estimate consensus procedure that considered all available study materials 3, including medical records. The severity of tics was rated with the Yale Global Tic Severity Scale(YGTSS) 4 for 24 of the 25 Tourette syndrome subjects studied. OCD symptoms were quantified using the Yale Brown Obsessive Compulsive Scale 5,

5 Cortical Thickness in Tourette Syndrome 2 6. The YGTSS does not query severity of face vs. trunk and body tics separately, but parents are asked to provide yes/no responses to questions regarding the types of tics their children exhibit. We created new measures for 21 of the Tourette syndrome subjects for whom data was available by summing the number of yes responses the parents endorsed for tics of the face (i.e., eye blinking, eye movements, nose movements, mouth movements, facial grimace, eye movements, mouth movements, facial movements or expressions), and a separate score for tics of the body and trunk (shoulder shrugs, arm movements, hand movements, abdominal tensing, leg foot or toe movements, head gestures or movements, shoulder movements, arm movements, hand movements, writing tics, dystonic posturing, bending or gyrating, rotating, leg or foot or toe movements, tic related compulsive behaviors, touching, tapping, grooming, evening up, copopraxia, self abusive behavior, paroxysms of tics). Presumably, children with higher scores exhibit more types of tics in each category, though the severity is not addressed with these new measures we created. ADHD symptoms were assessed with the Conners Parent and Teacher Rating Scales 7, 8, the Child Behavior Checklist 9 and the DuPaul Barkley ADHD Rating scale 10. These data were collected for both the control and Tourette syndrome groups. At the time of imaging, 11 of the 25 Tourette syndrome subjects were taking alpha agonists, typical neuroleptics, SSRIs, or some combination of these medications. Mean Full Scale intelligence quotient 11 for 23 of these subjects who underwent cognitive testing was 108 (SD = 15). Some of these subjects have been included in previous volumetric studies from our group 12.

6 Cortical Thickness in Tourette Syndrome 3 Brain imaging data were collected from thirty five control subjects (mean age 12.3 years, 7 to 21 years, 10 female) who were group matched on age and gender to the Tourette syndrome subjects. All were recruited from community households randomly selected from a telemarketing database 13. Subjects were excluded from participation if they had a history of concussion, seizure disorder, neurologic or medical illness, developmental delay, or current DSM IV based Axis I disorder based on a structured diagnostic interview that was either administered or reviewed by a board certified child and adult psychiatrist (BSP). Mean Full Scale intelligence quotient for 33 of these subjects who underwent cognitive testing was 119 (SD = 15). Informed parental consent and subject assent was obtained from all participants, and the study had the approval of the local institutional review board. To ensure that co morbid diagnoses of ADHD or OCD did not influence the findings for the diagnostic effects of Tourette syndrome on cortical thickness, separate analyses were conducted on a subset of 16 pure Tourette syndrome subjects (diagnosed with Tourette syndrome only and not ADHD or OCD, mean age 12.2 years, range 7 to 19 years; 4 female) and 19 controls (group matched by age and gender to the pure Tourette syndrome subjects; mean age 12.2, range 7 to 21 years; 7 female). Image Acquisition All subjects were scanned (by BSP) with a single 1.5 Tesla superconducting Magnetic Resonance Imaging (MRI) magnet (Signa; General Electric, Milwaukee, WI) located at Yale University. The MRI protocol collected

7 Cortical Thickness in Tourette Syndrome 4 included a whole brain 3D gradient echo (SPGR) T 1 weighted series reconstructed in the sagittal plane, with repetition time = 24 ms, echo time = 5 ms, number of excitations = 2, flip angle = 45 degrees, field of view of 30 cm, matrix = 256x192, 124 slices with slice thickness of 1.2 mm, no gaps, acquisition time, 19 minutes. Image Processing Details of the image analysis procedures have been described previously Briefly, the MR images from each individual were analyzed with a series of manual and automated procedures that included: (i) transforming brain volumes into a standardized 3D coordinate space 19 using a 12 parameter, linear, automated image registration algorithm 20 ; (ii) Semi automated tissue segmentation for each volume dataset to classify voxels based on signal intensity as most representative of gray matter, white matter, or cerebrospinal fluid 21 ; (iii) removing non brain tissue (i.e., scalp, orbits) and cerebellum, and excluding the left hemisphere from the right; (iv) automatically extracting the cortical surface of each hemisphere represented as a high resolution mesh of 131,072 triangulated elements spanning 65,536 surface points in each hemisphere 22 ; (v) tracing 35 sulcal and gyral landmarks on the lateral and inter hemispheric surfaces of each hemisphere; (vi) transforming image volumes back into their own native space of image acquisition by mathematically inverting the transformation which took them into standard space (step (i) above); (vii) spatially registering all segmented images and brain surfaces for each individual by defining 80 standardized, manually defined anatomical landmarks (40 in each hemisphere, the first and last

8 Cortical Thickness in Tourette Syndrome 5 points on each of 20 of the 35 sulcal lines drawn in each hemisphere) 23, 24 ; (viii) measuring cortical thickness, in millimeters, averaged within a 15 mm sphere attached to each cortical surface point (see below). Image analysts (JY and EK) who were blind to subject diagnosis, sex and age traced each of 17 sulci (Sylvian fissure, and central, pre central, post central, superior temporal sulcus (STS) main body, STS ascending branch, STS posterior branch, primary intermediate sulcus, secondary intermediate sulcus, inferior temporal, superior frontal, inferior frontal, intraparietal, transverse occipital, olfactory, occipito temporal, and collateral sulci) in each hemisphere on the lateral aspect of the surface rendering of each child s brain. An additional set of 12 sulci were outlined on each interhemispheric surface (callosal sulcus, inferior callosal outline, superior rostral sulcus, inferior rostral sulcus, paracentral sulcus, anterior and posterior segments of the cingulate sulcus, outer segment double parallel cingulate sulcus when present, parieto occipital sulcus, anterior and posterior segments of the calcarine sulcus, and the subparietal sulcus). In addition to contouring the major sulci, a set of 6 midline landmark curves bordering the longitudinal fissure were outlined in each hemisphere to establish limits of hemispheric gyri. Spatially registered gray scale image volumes in coronal, axial, and sagittal planes were available simultaneously to help distinguish anatomical features of the brain. We have developed detailed criteria for delineating the cortical lines, and for the starting and stopping points for each sulcus, using atlases of the brain surface as references 25, 26. These criteria and

9 Cortical Thickness in Tourette Syndrome 6 reliability measures have been described previously 24. Complete details of the written anatomical protocol can be obtained from the authors. The thickness of gray matter was calculated using the Eikonal Fire Equation 18, 27. Although the brain images acquired for this study had voxel dimensions of approximately 1 x 1 x 1.2 mm, we supersampled the imaging data to create voxel dimensions of 0.33 mm 3. The 3D Eikonal equation was applied only to voxels that segmented as gray matter, and a smoothing kernel was used to average gray matter thickness within a 15mm sphere at each point on the cortical surface. The cortical surface area within each sphere likely varied depending on its location within the 3 dimensional thickness volume for each subject. Nonetheless, these methods allowed us to calculate cortical thickness for each subject at an effective resolution much finer than that of the original voxel size in the image, given that the error associated with localizing anatomy on the inner and outer cortical surfaces is averaged with the unbiased error of all other voxels within the smoothing kernel. Points on the cortical surfaces surrounding and between the sulcal contours drawn on the surface of each individual brain were calculated using the averaged sulcal contours as anchors to drive models of the 3D cortical surface mesh from each subject into a common correspondence 18. This allowed the creation of average surface models, and the creation of maps of group differences for thickness of gray matter. To map gray matter thickness onto the surface rendering of each child s brain, the coordinate of each point on the cortical surface for each child (anatomically matched across individuals) was mapped to the same anatomical

10 Cortical Thickness in Tourette Syndrome 7 location in their thickness volume, and the average maximum thickness of gray matter within a 15mm sphere was calculated. In a previous report, we helped to establish the validity of these methods by showing close regional correspondence between maps of cortical thickness created for normally developing children in vivo 17 and for the post mortem data of Von Economo 28. In our earlier report 17, we also assessed the test retest reliability of measures of cortical thickness in individuals scanned twice at short time intervals, demonstrating maximum error estimates of 0.15 millimeters. Statistical Analyses Statistical maps of differences between Tourette syndrome and control groups were created for measures of gray matter thickness. Simple correlations between cortical thickness and group membership were created, but because groups differed significantly on intelligence quotient measures (p = 0.01), and because gray matter thickness has been shown to be related to intelligence quotient 29, subsequent analyses were conducted in which group differences in thickness were evaluated with intelligence quotient entered as a covariate. Note that for the 2 subjects in each group who did not have intelligence quotient scores, the mean intelligence quotient score for their respective groups (108 for the Tourette syndrome group and 119 for the control group) was used as an estimate to ensure maximal power in the cortical thickness analyses. Analysis of variance was used to compare a full model, which included group and intelligence quotient, with a reduced model that included only group. F ratios were computed at each point on the cortical surface and were converted to

11 Cortical Thickness in Tourette Syndrome 8 uncorrected p values. An uncorrected threshold of p=0.05 was used to illustrate the regions where group differences should be considered independent of intelligence quotient differences. Similar statistical analyses for group effects that were independent of intelligence quotient were conducted on the smaller subgroup of Tourette syndrome subjects who were unaffected with co occurring OCD or ADHD. Given the wide age range between childhood and late adolescence, we evaluated the effects of age x diagnosis interactions on cortical thickness. We also compared the full model containing age, diagnosis, and their interaction with a reduced model that did not include the interaction term. Statistical maps (uncorrected) allowed us to visualize the spatial patterns of group differences in thickness of gray matter, but we used permutation methods 30 to assess the significance of the statistical maps and to correct for multiple comparisons within anatomical regions of interest (ROI). Coarse ROIs were created from a probabilistic atlas for each individual and each hemisphere 31, and included the frontal lobe (ventral and dorsal regions separated by an axial plane passing through the intersection of the posterior extent of the inferior frontal sulcus and the precentral sulcus in each hemisphere), parietal lobe, temporal lobe, and occipital lobe. The new ROIs for all individuals were then averaged to create regional masks, and the ventral and dorsal frontal, parietal, and occipital ROIs were separated into medial and lateral regions. Permutation tests were used to evaluate the significance of group effects, independent of group differences in intelligence quotient, while correcting for

12 Cortical Thickness in Tourette Syndrome 9 multiple comparisons (i.e., over 65,000 tests in each hemisphere). It is not possible to perform an exact permutation test that separates the effects of intelligence quotient from the main effects of group (given that by definition, the main effects of group and intelligence quotient must be held constant at the same time). Approximate permutation tests, based on permutation of the residuals of these statistical models have been described and validated 32 34, and we have used these methods in other published reports 35. While holding constant the portions of variance in cortical thickness that the reduced model attributed to intelligence quotient, the associated residual variance in thickness not attributable to intelligence quotient was permuted randomly across all subjects irrespective of intelligence quotient. The new sets of observations generated by combining the permuted contribution to cortical thickness with the non permuted contribution associated with the main effects of intelligence quotient were then analyzed using the same statistical models as were used to analyze the original data. By combining a large number of such permutations (N=10,000), a distribution for the number of brain locations where the uncorrected p value was less than 0.05 was created. Based on this distribution and the number of such points observed in the original data, a p value was assigned for each of the ROIs. In order to further ensure that group effects were not carried by intelligence quotient differences, we created a new control group. Eliminating the 10 controls with the highest intelligence quotients resulted in groups that were equal in size (25 Tourette syndrome and 25 Controls), and not statistically

13 Cortical Thickness in Tourette Syndrome 10 different on intelligence quotient (Tourette syndrome mean intelligence quotient 107 control mean intelligence quotient 113, group difference p = 0.188). Finally, given the wide age range studied between childhood and late adolescence, we evaluated the effects of age x diagnosis interactions on cortical thickness. We compared the full model to predict cortical thickness using age, diagnosis, and their interaction with a reduced model that did not include the interaction term. We conducted similar permutation analyses on the age x group interactions by holding constant the portions of variance in cortical thickness that are attributed by the reduced model (without the age or group terms) to the interaction term, the associated residual variances in thickness not attributable to age or group were permuted randomly across all subjects irrespective of age or group. The new sets of observations generated by combining the permuted contribution to cortical thickness with the non permuted contribution associated with the main effects of age and group were then analyzed using the same statistical models as were used to analyze the original data. References: 1. Pauls, D.L. & Hurst, C.R. Schedule for Tourette and Other Behavioral Syndromes (Yale University Child Study Center, New Haven, Conn., 1996). 2. Kaufman, J., et al. Schedule for Affective Disorders and Schizophrenia for School Age Children Present and Lifetime Version (K SADS PL): initial reliability and validity data. J Am Acad Child Adolesc Psychiatry 36, (1997).

14 Cortical Thickness in Tourette Syndrome Leckman, J.F., Sholomskas, D., Thompson, W.D., Belanger, A. & Weissman, M.M. Best estimate of lifetime psychiatric diagnosis: a methodological study. Arch Gen Psychiatry 39, (1982). 4. Leckman, J.F., et al. The Yale Global Tic Severity Scale: initial testing of a clinician rated scale of tic severity. J Am Acad Child Adolesc Psychiatry 28, (1989). 5. Scahill, L., et al. Children's Yale Brown Obsessive Compulsive Scale: reliability and validity. J Am Acad Child Adolesc Psychiatry 36, (1997). 6. Goodman, W.K., et al. The Yale Brown Obsessive Compulsive Scale. I. Development, use, and reliability. Arch Gen Psychiatry 46, (1989). 7. Conners, C.K., Sitarenios, G., Parker, J.D. & Epstein, J.N. Revision and restandardization of the Conners Teacher Rating Scale (CTRS R): factor structure, reliability, and criterion validity. J Abnorm Child Psychol 26, (1998). 8. Conners, C.K., Sitarenios, G., Parker, J.D. & Epstein, J.N. The revised Conners' Parent Rating Scale (CPRS R): factor structure, reliability, and criterion validity. J Abnorm Child Psychol 26, (1998). 9. Achenback, T. & Edelbrock, C. Manual for the Child Behavior Checklist and Revised Child Behavior Profile (University of Vermont, Department of Psychiatry, Burlington, VT, 1983). 10. DuPaul, G.J. Parent and teacher ratings of ADHD symptoms: psychometric properties in a community based sample. Journal of Clinical Child Psychology 20, (1991).

15 Cortical Thickness in Tourette Syndrome Wechsler, D. Manual for the Wechsler Intelligence Scale for Children Third Edition (The Psychological Corporation, San Antonio, TX, 1991). 12. Peterson, B.S., et al. Regional brain and ventricular volumes in Tourette syndrome. Arch Gen Psychiatry 58, (2001). 13. Peterson, B.S., et al. Preliminary findings of antistreptococcal antibody titers and basal ganglia volumes in tic, obsessive compulsive, and attention deficit/hyperactivity disorders. Arch Gen Psychiatry 57, (2000). 14. Sowell, E.R., et al. Regional brain shape abnormalities persist into adolescence after heavy prenatal alcohol exposure. Cerebral Cortex 12, (2002). 15. Sowell, E.R., Thompson, P.M., Tessner, K.D. & Toga, A.W. Mapping continued brain growth and gray matter density reduction in dorsal frontal cortex: Inverse relationships during postadolescent brain maturation. J Neurosci 21, (2001). 16. Sowell, E.R., et al. Cortical Abnormalities in Children and Adolescents with Attention Deficit Hyperactivity Disorder. Lancet 362, (2003). 17. Sowell, E.R., et al. Longitudinal Mapping of Cortical Thickness and Brain Growth in Normal Children. Journal of Neuroscience 24, (2004). 18. Thompson, P.M., et al. Mapping cortical change in Alzheimer's disease, brain development, and schizophrenia. Neuroimage 23 Suppl 1, S2 18 (2004). 19. Mazziotta, J.C., Toga, A.W., Evans, A., Fox, P. & Lancaster, J. A probabilistic atlas of the human brain: theory and rationale for its development.

16 Cortical Thickness in Tourette Syndrome 13 The International Consortium for Brain Mapping (ICBM). Neuroimage 2, (1995). 20. Woods, R.P., Mazziotta, J.C. & Cherry, S.R. MRI PET registration with automated algorithm. Journal of Computer Assisted Tomography 17, (1993). 21. Sowell, E.R., et al. Localizing age related changes in brain structure between childhood and adolescence using statistical parametric mapping. Neuroimage 9, (1999). 22. MacDonald, D., Avis, D. & Evans, A. Multiple surface identification and matching in magnetic resonance images. Proceedings Visualization in Biomedical Computing 2359, (1994). 23. Sowell, E.R., et al. Mapping Cortical Change Across the Human Life Span. Nature Neuroscience 6, (2003). 24. Sowell, E.R., et al. Mapping sulcal pattern asymmetry and local cortical surface gray matter distribution in vivo: maturation in perisylvian cortices. Cereb Cortex 12, (2002). 25. Duvernoy, H.M., Cabanis, E.A. & Vannson, J.L. The human brain: surface, three dimensional sectional anatomy and MRI (Springer Verlag, Wien ; New York, 1991). 26. Ono, M., Kubik, S. & Abernathey, C.D. Atlas of the cerebral sulci (G. Thieme Verlag; Thieme Medical Publishers, Stuttgart New York, 1990). 27. Sapiro, G. Geometric Partial Differential Equations and Image Analysis (Cambridge University Press, 2001).

17 Cortical Thickness in Tourette Syndrome Von Economo, C.V. The Cytoarchitectonics of the Human Cerebral Cortex (Oxford Medical Publications, London, 1929). 29. Shaw, P., et al. Intellectual ability and cortical development in children and adolescents. Nature 440, (2006). 30. Bullmore, E.T., et al. Global, voxel, and cluster tests, by theory and permutation, for a difference between two groups of structural MR images of the brain. IEEE Trans Med Imaging 18, (1999). 31. Evans, A.C., Collins, D.L. & Holmes, C.J. Automatic 3D Regional MRI Segmentation and Statistical Probabilistic Anatomical Maps (Academic Press, New York, 1996). 32. Anderson, M.J. & Legendre, P. An Empirical Comparison of Permutation Methods for Tests of Partial Regression Coefficients in a Linear Model. Journal of Statistical Computation and Simulation 62, (1999). 33. Anderson, M.J. & Ter Braak, C.J. Permutation Tests for Multi Factorial Analysis of Variance. Journal of Statistical Computation and Simulation 73, (2003). 34. Freedman, D. & Lane, D. A Nonstochastic Interpretation of Reported Significance Levels. Journal of Business and Economic Statistics 1, (1983). 35. Sowell, E.R., et al. Sex Differences in Cortical Thickness Mapped in 176 Healthy Individuals between 7 and 87 Years of Age. Cereb Cortex (2006).